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The rules stored in the rule base have an impact on classification efficiency.
Consequently, the proposed method showed relatively very high classification efficiency if the SVM module is designed with considering THV values.
Designing a convenient and automatic recognition system of herbs species is essential since this will improve herb species classification efficiency.
However, there are still amounts of fine coal particles which cannot be removed due to low classification efficiency.
Dynamic boundaries at this level resulted in a nearly 2-fold increase in classification efficiency over static boundaries.
Calculation was done about the circulating ratio within the VSM and classification efficiency of the classifier with several surveys.
A lab experimental work has validated the chosen models in simulation by comparing the classification efficiency results.
The experimental results indicate that the insertion of fine particle outlet significantly enhanced the particle classification efficiency.
In particular, the proposed approach helps to increase the classification accuracy, while enhancing classification efficiency by requiring considerably less features.
Statistically designed experiments were carried out and their effects on performance in terms of yield to under flow, cut size (D50) and classification efficiency (EP) has been evaluated.
In addition, both the coal type and the roller load pressure have indirectly influence on the classification efficiency by affecting the flow rate of the classifier feed.
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